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I am predicting the electrical load and I also use the predicted temperature as one of the input feature. For example, I want to predict the electrical for tomorrow. I use the predicted temperature for tomorrow as an input feature.

Since in the real application the prediceted temperature will have an error, I want to add a noise to the temperature. However, I dont know how much noise I should add to the temperature. Do you have any suggestion for this?

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  • $\begingroup$ What do you hope to accomplish by adding this noise? $\endgroup$
    – whuber
    May 11 at 21:15
  • $\begingroup$ Since the predicted value for temperature is not exactly same as the actual value, and electric load has a powerful correlation with temperature. If I add noise to temperature, probably my model will be more robust. $\endgroup$
    – sadcow
    May 12 at 1:38
  • $\begingroup$ It's hard to see how injecting noise into this analysis could improve it. $\endgroup$
    – whuber
    May 12 at 11:56

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